Senior Data Platform Engineer

Wrapbook

1d•$148,800 - $227,800•Remote

About The Position

Our mission at Wrapbook is to increase the prosperity of the project economy. A significant shift has occurred within the workforce recently and 50M Americans are now engaged in freelance or project-based work. The popularity of project based employment has introduced flexibility for both employers and employees but also added complexities from a compensation and administrative standpoint. Our vertical fintech platform enables companies to seamlessly onboard, pay and insure their workforces. We’re building the best product for the entertainment industry but operate in a 50B market and have big goals we want to achieve. With legacy competition slow to react and over 30M raised from Andreessen Horowitz, Equal Ventures, Uncork Capital, Jeffrey Katzenberg and CAA co-founder Michael Ovitz, we are at an exciting stage of growth and there isn’t a better time to join! The Opportunity — (Remote - Canada) We are looking for a Senior Data Platform Engineer who will own the end-to-end design, build, and operation of a unified data platform at Wrapbook. Today we have pieces of a data platform in place, but nothing that ties everything together in a scalable, cohesive way. This is a green-field opportunity for someone who has built data platforms before and is energized by cross-functional collaboration and the challenge of balancing immediate needs with long-term architecture. The work is roughly 80% platform engineering (infrastructure, tooling, automation) and 20% data engineering (pipelines and transformations), partnering closely with Product Engineering, Analytics, Compliance, and Security.

Requirements

A track record of building and operating data platforms in fast-growing or early-stage environments — you've done this before and know what good looks like.
Strong coding fluency in Python (preferred) and at least one of Java or Scala, with deep knowledge of relational databases (especially PostgreSQL) and hands-on experience with tools like Dagster, Airbyte, Airflow, and dbt.
Infrastructure automation expertise — experience with Terraform, Ansible, or similar tooling, and comfort working on AWS or other major cloud platforms.
The ability to design scalable data models and system architectures that balance performance, cost, and governance.
A self-directed, solution-oriented approach — you're comfortable with ambiguity, propose solutions with clear trade-offs, and drive execution with minimal oversight.
A collaborative mindset — proven experience partnering across analytics, product engineering, compliance, and security to align architecture with business objectives.
An AI-centric workflow — you embrace AI coding assistants (such as Claude Code) as essential tools, using them to streamline repetitive work, orchestrate multi-stage tasks, and connect systems and services.
Excellent communication skills and availability to collaborate effectively with a team.

Responsibilities

Design and build an integrated data platform — unify our existing tools and pipelines into a cohesive, scalable architecture that serves the entire organization.
Own data pipelines and SLAs end to end, ensuring data moves reliably between systems with clear expectations and well-defined metrics.
Define and manage data contracts that prevent upstream changes from breaking downstream analytics, establishing the standards the team builds on.
Shape the data strategy and platform roadmap — research new technologies, evaluate trade-offs, and introduce tools and frameworks as the platform evolves.
Stand up observability across the platform — robust monitoring and telemetry so teams can understand system health and troubleshoot quickly.
Partner with Product, Compliance, and Security on data governance, balancing user needs with regulatory requirements.
Participate in an on-call rotation to support production data systems.